class_docstr: An Item-Item Recommender on Cosine distances between items
code: def fit(self, counts, show_progress=True, callback=None):
      # cosine distance is just the dot-product of a normalized matrix
      ItemItemRecommender.fit(
          self, normalize(counts.T).T, show_progress, callback
      )
  
imports: import numpy
  from numpy import bincount, log, log1p, sqrt
  from scipy.sparse import coo_matrix, csr_matrix
  from ._nearest_neighbours import NearestNeighboursScorer, all_pairs_knn
  from .recommender_base import RecommenderBase
  from .utils import _batch_call
label_desc: Use image node_id 1 for calling the CosineRecommender obj's underlying member method code with example usage: obj.fit(counts, show_progress, callback) without return types